{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d5772e3d",
   "metadata": {},
   "source": [
    "### 定义sigmoid函数 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3e1f8529",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def sigmoid(x):\n",
    "    return 1.0/(1+np.exp(-x))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3e41e1f",
   "metadata": {},
   "source": [
    "### 生成实验数据，计算函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9d6d01be",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sigmoid Function Input :: [-1.00000000e+01 -9.90000000e+00 -9.80000000e+00 -9.70000000e+00\n",
      " -9.60000000e+00 -9.50000000e+00 -9.40000000e+00 -9.30000000e+00\n",
      " -9.20000000e+00 -9.10000000e+00 -9.00000000e+00 -8.90000000e+00\n",
      " -8.80000000e+00 -8.70000000e+00 -8.60000000e+00 -8.50000000e+00\n",
      " -8.40000000e+00 -8.30000000e+00 -8.20000000e+00 -8.10000000e+00\n",
      " -8.00000000e+00 -7.90000000e+00 -7.80000000e+00 -7.70000000e+00\n",
      " -7.60000000e+00 -7.50000000e+00 -7.40000000e+00 -7.30000000e+00\n",
      " -7.20000000e+00 -7.10000000e+00 -7.00000000e+00 -6.90000000e+00\n",
      " -6.80000000e+00 -6.70000000e+00 -6.60000000e+00 -6.50000000e+00\n",
      " -6.40000000e+00 -6.30000000e+00 -6.20000000e+00 -6.10000000e+00\n",
      " -6.00000000e+00 -5.90000000e+00 -5.80000000e+00 -5.70000000e+00\n",
      " -5.60000000e+00 -5.50000000e+00 -5.40000000e+00 -5.30000000e+00\n",
      " -5.20000000e+00 -5.10000000e+00 -5.00000000e+00 -4.90000000e+00\n",
      " -4.80000000e+00 -4.70000000e+00 -4.60000000e+00 -4.50000000e+00\n",
      " -4.40000000e+00 -4.30000000e+00 -4.20000000e+00 -4.10000000e+00\n",
      " -4.00000000e+00 -3.90000000e+00 -3.80000000e+00 -3.70000000e+00\n",
      " -3.60000000e+00 -3.50000000e+00 -3.40000000e+00 -3.30000000e+00\n",
      " -3.20000000e+00 -3.10000000e+00 -3.00000000e+00 -2.90000000e+00\n",
      " -2.80000000e+00 -2.70000000e+00 -2.60000000e+00 -2.50000000e+00\n",
      " -2.40000000e+00 -2.30000000e+00 -2.20000000e+00 -2.10000000e+00\n",
      " -2.00000000e+00 -1.90000000e+00 -1.80000000e+00 -1.70000000e+00\n",
      " -1.60000000e+00 -1.50000000e+00 -1.40000000e+00 -1.30000000e+00\n",
      " -1.20000000e+00 -1.10000000e+00 -1.00000000e+00 -9.00000000e-01\n",
      " -8.00000000e-01 -7.00000000e-01 -6.00000000e-01 -5.00000000e-01\n",
      " -4.00000000e-01 -3.00000000e-01 -2.00000000e-01 -1.00000000e-01\n",
      " -3.55271368e-14  1.00000000e-01  2.00000000e-01  3.00000000e-01\n",
      "  4.00000000e-01  5.00000000e-01  6.00000000e-01  7.00000000e-01\n",
      "  8.00000000e-01  9.00000000e-01  1.00000000e+00  1.10000000e+00\n",
      "  1.20000000e+00  1.30000000e+00  1.40000000e+00  1.50000000e+00\n",
      "  1.60000000e+00  1.70000000e+00  1.80000000e+00  1.90000000e+00\n",
      "  2.00000000e+00  2.10000000e+00  2.20000000e+00  2.30000000e+00\n",
      "  2.40000000e+00  2.50000000e+00  2.60000000e+00  2.70000000e+00\n",
      "  2.80000000e+00  2.90000000e+00  3.00000000e+00  3.10000000e+00\n",
      "  3.20000000e+00  3.30000000e+00  3.40000000e+00  3.50000000e+00\n",
      "  3.60000000e+00  3.70000000e+00  3.80000000e+00  3.90000000e+00\n",
      "  4.00000000e+00  4.10000000e+00  4.20000000e+00  4.30000000e+00\n",
      "  4.40000000e+00  4.50000000e+00  4.60000000e+00  4.70000000e+00\n",
      "  4.80000000e+00  4.90000000e+00  5.00000000e+00  5.10000000e+00\n",
      "  5.20000000e+00  5.30000000e+00  5.40000000e+00  5.50000000e+00\n",
      "  5.60000000e+00  5.70000000e+00  5.80000000e+00  5.90000000e+00\n",
      "  6.00000000e+00  6.10000000e+00  6.20000000e+00  6.30000000e+00\n",
      "  6.40000000e+00  6.50000000e+00  6.60000000e+00  6.70000000e+00\n",
      "  6.80000000e+00  6.90000000e+00  7.00000000e+00  7.10000000e+00\n",
      "  7.20000000e+00  7.30000000e+00  7.40000000e+00  7.50000000e+00\n",
      "  7.60000000e+00  7.70000000e+00  7.80000000e+00  7.90000000e+00\n",
      "  8.00000000e+00  8.10000000e+00  8.20000000e+00  8.30000000e+00\n",
      "  8.40000000e+00  8.50000000e+00  8.60000000e+00  8.70000000e+00\n",
      "  8.80000000e+00  8.90000000e+00  9.00000000e+00  9.10000000e+00\n",
      "  9.20000000e+00  9.30000000e+00  9.40000000e+00  9.50000000e+00\n",
      "  9.60000000e+00  9.70000000e+00  9.80000000e+00  9.90000000e+00]\n",
      "Sigmoid Function Output :: [4.53978687e-05 5.01721647e-05 5.54485247e-05 6.12797396e-05\n",
      " 6.77241496e-05 7.48462275e-05 8.27172229e-05 9.14158739e-05\n",
      " 1.01029194e-04 1.11653341e-04 1.23394576e-04 1.36370327e-04\n",
      " 1.50710358e-04 1.66558065e-04 1.84071905e-04 2.03426978e-04\n",
      " 2.24816770e-04 2.48455082e-04 2.74578156e-04 3.03447030e-04\n",
      " 3.35350130e-04 3.70606141e-04 4.09567165e-04 4.52622223e-04\n",
      " 5.00201107e-04 5.52778637e-04 6.10879359e-04 6.75082731e-04\n",
      " 7.46028834e-04 8.24424686e-04 9.11051194e-04 1.00677082e-03\n",
      " 1.11253603e-03 1.22939862e-03 1.35851995e-03 1.50118226e-03\n",
      " 1.65880108e-03 1.83293894e-03 2.02532039e-03 2.23784852e-03\n",
      " 2.47262316e-03 2.73196076e-03 3.01841632e-03 3.33480731e-03\n",
      " 3.68423990e-03 4.07013772e-03 4.49627316e-03 4.96680165e-03\n",
      " 5.48629890e-03 6.05980149e-03 6.69285092e-03 7.39154134e-03\n",
      " 8.16257115e-03 9.01329865e-03 9.95180187e-03 1.09869426e-02\n",
      " 1.21284350e-02 1.33869178e-02 1.47740317e-02 1.63024994e-02\n",
      " 1.79862100e-02 1.98403057e-02 2.18812709e-02 2.41270214e-02\n",
      " 2.65969936e-02 2.93122308e-02 3.22954647e-02 3.55711893e-02\n",
      " 3.91657228e-02 4.31072549e-02 4.74258732e-02 5.21535631e-02\n",
      " 5.73241759e-02 6.29733561e-02 6.91384203e-02 7.58581800e-02\n",
      " 8.31726965e-02 9.11229610e-02 9.97504891e-02 1.09096821e-01\n",
      " 1.19202922e-01 1.30108474e-01 1.41851065e-01 1.54465265e-01\n",
      " 1.67981615e-01 1.82425524e-01 1.97816111e-01 2.14165017e-01\n",
      " 2.31475217e-01 2.49739894e-01 2.68941421e-01 2.89050497e-01\n",
      " 3.10025519e-01 3.31812228e-01 3.54343694e-01 3.77540669e-01\n",
      " 4.01312340e-01 4.25557483e-01 4.50166003e-01 4.75020813e-01\n",
      " 5.00000000e-01 5.24979187e-01 5.49833997e-01 5.74442517e-01\n",
      " 5.98687660e-01 6.22459331e-01 6.45656306e-01 6.68187772e-01\n",
      " 6.89974481e-01 7.10949503e-01 7.31058579e-01 7.50260106e-01\n",
      " 7.68524783e-01 7.85834983e-01 8.02183889e-01 8.17574476e-01\n",
      " 8.32018385e-01 8.45534735e-01 8.58148935e-01 8.69891526e-01\n",
      " 8.80797078e-01 8.90903179e-01 9.00249511e-01 9.08877039e-01\n",
      " 9.16827304e-01 9.24141820e-01 9.30861580e-01 9.37026644e-01\n",
      " 9.42675824e-01 9.47846437e-01 9.52574127e-01 9.56892745e-01\n",
      " 9.60834277e-01 9.64428811e-01 9.67704535e-01 9.70687769e-01\n",
      " 9.73403006e-01 9.75872979e-01 9.78118729e-01 9.80159694e-01\n",
      " 9.82013790e-01 9.83697501e-01 9.85225968e-01 9.86613082e-01\n",
      " 9.87871565e-01 9.89013057e-01 9.90048198e-01 9.90986701e-01\n",
      " 9.91837429e-01 9.92608459e-01 9.93307149e-01 9.93940199e-01\n",
      " 9.94513701e-01 9.95033198e-01 9.95503727e-01 9.95929862e-01\n",
      " 9.96315760e-01 9.96665193e-01 9.96981584e-01 9.97268039e-01\n",
      " 9.97527377e-01 9.97762151e-01 9.97974680e-01 9.98167061e-01\n",
      " 9.98341199e-01 9.98498818e-01 9.98641480e-01 9.98770601e-01\n",
      " 9.98887464e-01 9.98993229e-01 9.99088949e-01 9.99175575e-01\n",
      " 9.99253971e-01 9.99324917e-01 9.99389121e-01 9.99447221e-01\n",
      " 9.99499799e-01 9.99547378e-01 9.99590433e-01 9.99629394e-01\n",
      " 9.99664650e-01 9.99696553e-01 9.99725422e-01 9.99751545e-01\n",
      " 9.99775183e-01 9.99796573e-01 9.99815928e-01 9.99833442e-01\n",
      " 9.99849290e-01 9.99863630e-01 9.99876605e-01 9.99888347e-01\n",
      " 9.99898971e-01 9.99908584e-01 9.99917283e-01 9.99925154e-01\n",
      " 9.99932276e-01 9.99938720e-01 9.99944551e-01 9.99949828e-01]\n"
     ]
    }
   ],
   "source": [
    "sigmoid_inputs = np.arange(-10, 10, 0.1)\n",
    "sigmoid_outputs = sigmoid(sigmoid_inputs)\n",
    "print(\"Sigmoid Function Input :: {}\".format(sigmoid_inputs))\n",
    "print(\"Sigmoid Function Output :: {}\".format(sigmoid_outputs))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20d591eb",
   "metadata": {},
   "source": [
    "### 画出Sigmoid函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "008a4e6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nZh/qqePumo9ApBPzKmrIM7hwggaZk/SWSCK4JW65BPgYweBzItKJZyqqKR/VjwE9i6MORaRTiQw6t7RN0ctmtihJ8YhkhQ0732VVdR3f/Iim7pD0l8h8BP3iVvOAqUDvpEUkkgXmVVQDqNuoZIREmobizwiagXXAjckJRyQ7zKuoYcLQXpT16x51KCIHlUjT0JhUBCKSLbbV1fPaxt189YJjog5FJCGdJoJwWOgvARPDogqC0UI1SqhIB+avCKekPF69hSQzdDjEhJmdwftj/twfPgAWhdtEpB3zKmoY1b87xw4uPXhlkTTQ2RnBD4GPuvvrcWVzzOwJ4B4+PKS0SM6rrW/ilXd28JkzxmhKSskYnQ0616tNEgDA3ZfxwSEnRCT0wqptNLU4F09Us5Bkjs4SgZnZh+bVC7uTJjJqqUjOmVdRzcDSYk4q05SUkjk6+0L/MfCMmZ1jZqXh41yCuYp/nIrgRDJJfVMLL67ezkUTBpOnKSklg3Q26NxsM9sCfJug15ADK4DvuPufUhSfSMb425od7NeUlJKBOu0+6u5/Bv6colhEMtq8impKSwo4baympJTMorZ+kS7Q3BLj2ZU1nD9+EEUF+m8lmUWfWJEusHj9bnbvb1KzkGQkJQKRLjCvopqigjzOOUZTUkrm6WzO4k6nj3T3H3V9OCKZx92Zv6KGs8cNoEdxIuM4iqSXzs4ISsNHOfAFYHj4+DwwJfmhiWSG5VW1VO05wHQ1C0mG6qz76P8DMLMFwBR3rwvXbweeSkl0IhlgXkV1MCXlcbqbWDJTItcIBgONceuNYZmIECSCk0f3o1+PoqhDETksiTRo3k8w4ugT4fpHgfuSFZBIJlm7fR9rtu3jtssmRB2KyGFLZGKa/zCzp4GzwqLPtDcYnUgumldRA8B0DTInGayzXkO93L02HGRuffho3dbP3XclPzyR9Davoprjh/diRF9NSSmZq7Mzgt8BlxHMWexA/ChaDoxNYlwiaa96bz3LNu3hXy7SlJSS2TrrNXRZ+Kw5i0XaMX9FNQAXH69uo5LZErr7xcyuAM4OV18MB6MTyWnzKmoYM6AH4wb1jDoUkSNy0O6jZvY94CsEQ1CvAL5iZt9NdmAi6Wzv/iYWrt3J9ImDNSWlZLxEzgguBSa7ewzAzH4DvA78ezIDE0ln81fW0BxzZuhuYskCiQ461yduuXcS4hDJKH9ZvpVhvUuYXNYn6lBEjlgiieA/gdfN7L7wbGAp8B+JvLmZzTCz1WZWaWa3dlLvY2bmZlaeWNgi0amrb2LB2zuYcfxQNQtJVkjkhrKHzOxF4OSw6N/cvfpgrzOzfOAu4CJgM7DYzOa4+4o29UoJrkG8eoixi0Ti+VXbaGyJcckJahaS7JBo01DrIOsFwOlmdlUCr5kGVLr7WndvBB4Grmyn3reBO4H6BGMRidTTb1UzqLSYqSP7Rh2KSJc46BmBmd0LTAIqgFhY7MAfDvLS4cCmuPXNwClt3nsKUObuT5nZ1zqJYRYwC2DkyJEHC1kkafY3NvPi29u4ZmoZeXlqFpLskEivoVPdvctH1DKzPOBHwA0Hq+vus4HZAOXl5d7VsYgk6qXV26lvUrOQZJdEmoZeMbPDSQRVQFnc+oiwrFUpcDzwopmtB04F5uiCsaSzucur6dejiGmj+0UdikiXSXQY6lfMrBpoIBhzyN190kFetxgYZ2ZjCBLATOAfWze6+15gQOt6eEH6Fndfckg/gUiK1De18PzKGq6YPIyCfE33LdkjkUTwK+B64C3ev0ZwUO7ebGY3AfOAfOBed68wszuAJe4+53ACFonKX9fs4N3GFmYcPzTqUES6VCKJYPvhfmm7+1xgbpuy2zqoe+7h7EMkVZ5evpXe3Qo5/aj+UYci0qUSSQSvm9nvgD8RNA0B4O4H6zUkkjUam2PMX1HD9AlDKFSzkGSZRBJBN4IEMD2uLJHuoyJZ4+/v7KCuvplL1VtIslAidxZ/JhWBiKSzp9+qpmdxAWeOG3DwyiIZJpEbyn7WTvFeggu+T3Z9SCLppaG5hb9UVHPhcYMoLsiPOhyRLpdIY2cJMBlYEz4mEdwTcKOZ/SRpkYmkiQVv72DvgSaunDw86lBEkiKRawSTgDPcvQXAzH4B/BU4k6BLqUhWm/PGFvp2L1SzkGStRM4I+gLxc/H1APqFiaGh/ZeIZIf9jc08u6KGS08Yqt5CkrUSOSP4PrAsvPPXCOYu/q6Z9QCeTWJsIpGbv6KGA00tXHHisKhDEUmaRHoN/crM5hIMKw3w7+6+JVzucMRQkWwwZ9kWhvYu4WSNLSRZrMNzXTMbHz5PAYYSDCm9CRgSlolktT37G1mwZjuXnzhMQ05LVuvsjOBmgjkAftjONgfOT0pEImni6eXVNLW4moUk63WYCNx9Vvh8XurCEUkff3y9irEDejBxWK+oQxFJqs6ahk42syFx658ysyfN7GdmpgZTyWobd+7n1XW7uGrKcE1QL1mvs/5w9wCNAGZ2NvA9grkJ9hLOFiaSrR5/bTNmcNWUEVGHIpJ0nV0jyHf3XeHydcBsd38ceNzMliU9MpGIxGLOY0s3c+bRAxjWp1vU4YgkXWdnBPlm1pooLgCej9uWyP0HIhlp4bqdVO05wNVTdTYguaGzL/SHgJfMbAdwgGBYCczsaILmIZGs9NiSzZQWF3DxRA05Lbmhs15D/2FmzxHcQ/CMu3u4KQ/4ciqCE0m1uvom5i7fyj+cNIKSQo00Krmh0yYed1/YTtnbyQtHJFpz39pKfVNMzUKSUzSKlkicR5dsZuzAHkwZ2SfqUERSRolAJLRyay1LN+xm5sllundAcooSgUjogYUbKCrI45qpZVGHIpJSSgQiBBeJ//h6FZdPGkbfHkVRhyOSUkoEIgTjCr3b2ML1p42KOhSRlFMikJzn7vx24QZOGN6bE0f0jjockZRTIpCct2jdLt6u2cf1p47SRWLJSUoEkvMeeHUjvUoKuFzzDkiOUiKQnFa15wBz39rKNeVldCvSncSSm5QIJKfd+7d1AHz2zDERRyISHSUCyVl79zfx0KKNXHHiMIZruGnJYUlNBGY2w8xWm1mlmd3azvabzWyFmb1pZs+ZmfruSco88OoG9je2MOvssVGHIhKppCUCM8sH7gIuASYAHzezCW2qvQ6Uu/sk4DHg+8mKRyRefVMLv355PeccM5DjhmpOYsltyTwjmAZUuvtad28EHgaujK/g7i+4+/5wdSGgIR8lJZ54vYod+xr4Z50NiCQ1EQwHNsWtbw7LOnIj8HR7G8xslpktMbMl27dv78IQJRc1t8SYvWAtJwzvzWlH9Y86HJHIpcXFYjP7JFAO/KC97e4+293L3b184MCBqQ1Oss4Tr1exbse7fOm8o3QDmQjJnXu4CogfxnFEWPYBZnYh8A3gHHdvSGI8IjQ2x/jpc2s4YXhvTUUpEkrmGcFiYJyZjTGzImAmMCe+gpmdBNwDXOHu25IYiwgAjyzZxObdB/iX6cfobEAklLRE4O7NwE3APGAl8Ki7V5jZHWZ2RVjtB0BP4PdmtszM5nTwdiJHrL6phZ8/v4aTR/flnGPUxCjSKplNQ7j7XGBum7Lb4pYvTOb+ReL99pUN1NQ28NOZJ+lsQCROWlwsFkm2vfub+MVL73DWuAGcOlY9hUTiKRFITvjxs2+zZ38j/zZjfNShiKQdJQLJeiu31nL/K+v5x1NGcvxwTTwj0pYSgWQ1d+dbcyro3a2QW6YfG3U4ImlJiUCy2p/e3Mqidbv42sXj6dNdk9KLtEeJQLJWbX0T331qJccP78V1J5cd/AUiOSqp3UdFonTHn1awfV8Dd18/lfw8dRcV6YjOCCQrzV9Rw2NLN/PFc49iclmfqMMRSWtKBJJ1du5r4Ot/eJOJw3rx5fPHRR2OSNpT05BkFXfnG08sp/ZAMw/+02SKCvS3jsjB6H+JZJX7X9nAXyqquXn6MRw7pDTqcEQyghKBZI1F63bx7T+v4MLjBjHrLM08JpIoJQLJClv3HuCLDy5lZL/u/Oi6yeSpl5BIwnSNQDJefVMLX3jgNQ40tvDQ506lV0lh1CGJZBQlAsloTS0xvvTga7yxeQ+/+MRUxg3WdQGRQ6WmIclYsZhzy+/f4LlV27jjyuOZcbymnhQ5HEoEkpHcndv/VMGTy7bwtYuP5fpTR0UdkkjGUtOQZJyWmPPNPy7noUUb+eezx/LFc4+KOiSRjKZEIBmlvqmFrzz8OvMqavjSeUdxy/RjNe2kyBFSIpCMsWd/I7N+u5RF63bxrcsn8JkzxkQdkkhWUCKQjLBs0x6+9OBrbKur56czJ3Pl5OFRhySSNZQIJK25O/e/soHvPLWCQaUlPPb50zlRo4mKdCklAklbm3bt5xt/XM6Ct7dz/vhB/OjaEzXLmEgSKBFI2mmJOff9fT3/NW81ZnD75RP41GmjNWyESJIoEUjacHeeWVHDD+atpnLbPs47diDf+YcTGN6nW9ShiWQ1JQKJXCzmvPT2dn72/Bpe37iHsQN7cPcnp3DxxCHqGiqSAkoEEpn9jc388fUt/Opva3ln+7sM7V3CnR87gY9NGUFBvm56F0kVJQJJqVjMWbhuJ394rYqn39rKu40tHD+8Fz+dOZlLTxhKoRKASMopEUjSvdvQzN/f2clzK2t4duU2duxroGdxAZdNGsbV5SMoH9VXTUAiEVIikC63Z38ji9fvZvH6Xby6bhfLq/bSEnNKiws459iBTJ84hIuOG0y3ovyoQxURlAjkCOxvbGbjrv1UbtvHqq11rKquZeXWOqr2HACgKD+PyWV9+Pw5Yzlt7ACmjemnyeRF0lBSE4GZzQB+CuQDv3T377XZXgzcD0wFdgLXufv6ZMYkB+fu7GtoZntdA9vqGtgePrbVNVBTW8/GXfvZsHM/O/Y1vPea/DzjqIE9mDqqL584dSRTR/blxLI+lBTqr36RdJe0RGBm+cBdwEXAZmCxmc1x9xVx1W4Edrv70WY2E7gTuC5ZMWUad6c55rSEj+b3nmPBc0u4zf299caWGPVNLdQ3tdDQHCw3NMWobw6fm1qob26hvilGXX0TdfXN1NY3UXugmbr6Jmrrm6k90ERzzD8UT2G+Mai0hLJ+3Th//EBG9e9BWb/ujB3Qg3GDe1JcoC99kUyUzDOCaUClu68FMLOHgSuB+ERwJXB7uPwY8HMzM3f/8LfQEXp08SbuWfAOAB7+07oTd8eB1r06jvv7653WeW97WPre9vdf07o9fr11/x+qgxOLQXMsRjvfxV0iP88oKcijtKSQXt0KKC0pZEDPIsYO7EFpSQG9Sgrp3a2QQb2KGdizJHwupne3Qt3dK5KFkpkIhgOb4tY3A6d0VMfdm81sL9Af2BFfycxmAbMARo4ceVjB9O1RxPghvSD8HrPgfVtXMXu/rHU7Bq013t/epszeq/2BOkGpvVdG/Hu3s/29MjPy84yCvOA534z8/Nb1vPfKC/KMvLh6BXl55OdBUUEeJQX5FBfmU1KYR3FB8FxSmE9JYT7FBXnqoikiH5ARF4vdfTYwG6C8vPyw/k6+aMJgLpowuEvjEhHJBsn807AKKItbHxGWtVvHzAqA3gQXjUVEJEWSmQgWA+PMbIyZFQEzgTlt6swBPh0uXw08n4zrAyIi0rGkNQ2Fbf43AfMIuo/e6+4VZnYHsMTd5wC/An5rZpXALoJkISIiKZTUawTuPheY26bstrjleuCaZMYgIiKdU/cREZEcp0QgIpLjlAhERHKcEoGISI6zTOutaWbbgQ2H+fIBtLlrOY2ka2yK69AorkOXrrFlW1yj3H1gexsyLhEcCTNb4u7lUcfRnnSNTXEdGsV16NI1tlyKS01DIiI5TolARCTH5VoimB11AJ1I19gU16FRXIcuXWPLmbhy6hqBiIh8WK6dEYiISBtKBCIiOS7rEoGZXWNmFWYWM7PyNtu+bmaVZrbazC7u4PVjzOzVsN4j4RDaXR3jI2a2LHysN7NlHdRbb2ZvhfWWdHUcHezzdjOriovv0g7qzQiPY6WZ3ZqCuH5gZqvM7E0ze8LM+nRQLyXH7GA/v5kVh7/nyvDzNDpZscTts8zMXjCzFeH/ga+0U+dcM9sb9/u9rb33SlJ8nf5uLPCz8Ji9aWZTUhDTsXHHYpmZ1ZrZV9vUSckxM7N7zWybmS2PK+tnZvPNbE343LeD1346rLPGzD7dXp1OuXtWPYDjgGOBF4HyuPIJwBtAMTAGeAfIb+f1jwIzw+W7gS8kOd4fArd1sG09MCDFx+924JaD1MkPj99YoCg8rhOSHNd0oCBcvhO4M6pjlsjPD3wRuDtcngk8koLf3VBgSrhcCrzdTlznAn9O5Wcq0d8NcCnwNMHsracCr6Y4vnygmuDGq5QfM+BsYAqwPK7s+8Ct4fKt7X3ugX7A2vC5b7jc91D2nXVnBO6+0t1Xt7PpSuBhd29w93VAJTAtvoIFkwqfDzwWFv0G+GiyYg33dy3wULL2kSTTgEp3X+vujcDDBMc3adz9GXdvDlcXEsx4F5VEfv4rCT4/EHyeLrDWSauTxN23uvtr4XIdsJJgXvBMcSVwvwcWAn3MbGgK938B8I67H+7IBUfE3RcQzMsSL/5z1NH30cXAfHff5e67gfnAjEPZd9Ylgk4MBzbFrW/mw/9J+gN74r5w2qvTlc4Catx9TQfbHXjGzJaa2awkxtHWTeGp+b0dnIomciyT6bMEfzm2JxXHLJGf/7064edpL8HnKyXCpqiTgFfb2Xyamb1hZk+b2cRUxcTBfzdRf65m0vEfZVEds8HuvjVcrgbam3j9iI9bRkxe35aZPQsMaWfTN9z9yVTH054EY/w4nZ8NnOnuVWY2CJhvZqvCvxqSFhvwC+DbBP9pv03QdPXZI93nkcbVeszM7BtAM/BgB2+TlGOWScysJ/A48FV3r22z+TWCpo994fWfPwLjUhRa2v5uwmuBVwBfb2dzlMfsPe7uZpaU/v4ZmQjc/cLDeFkVUBa3PiIsi7eT4HS0IPwrrr06XRKjmRUAVwFTO3mPqvB5m5k9QdAkccT/cRI9fmb2v8Cf29mUyLHs8rjM7AbgMuACDxtH23mPpByzNhL5+VvrbA5/170JPl9JZWaFBEngQXf/Q9vt8YnB3eea2f+Y2QB3T/rgagn8bpLyuUrQJcBr7l7TdkOUxwyoMbOh7r41bCbb1k6dKoLrGK1GEFwjTVguNQ3NAWaGvTnGEGT0RfEVwi+XF4Crw6JPA8k6w7gQWOXum9vbaGY9zKy0dZngYuny9up2pTZtsv/QwT4XA+Ms6GFVRHBKPSfJcc0A/hW4wt33d1AnVccskZ9/DsHnB4LP0/MdJa+uEl6D+BWw0t1/1EGdIa3XKsxsGsF3QCoSVCK/mznAp8LeQ6cCe+OaRZKtw7PzqI5ZKP5z1NH30Txgupn1DZtyp4dliUv2lfBUPwi+vDYDDUANMC9u2zcIenusBi6JK58LDAuXxxIkiErg90BxkuK8D/h8m7JhwNy4ON4IHxUEzSOpOH6/Bd4C3gw/hEPbxhauX0rQK+WdVMQW/j42AcvCx91t40rlMWvv5wfuIEhUACXh56cy/DyNTcExOpOgSe/NuON0KfD51s8acFN4bN4guOh+eoo+V+3+btrEZsBd4TF9i7hef0mOrQfBF3vvuLKUHzOCRLQVaAq/w24kuK70HLAGeBboF9YtB34Z99rPhp+1SuAzh7pvDTEhIpLjcqlpSERE2qFEICKS45QIRERynBKBiEiOUyIQEclxSgSSsczsGxaMsvlmOCrkKWH5L81sQpL3PdfaGQHVgtFbb0m0vAviuMHMhnX1+0puycg7i0XM7DSCu4ynuHuDmQ0gGAkUd/+nZO/f3dsdnjsCNxDcmLUl4jgkg+mMQDLVUGCHuzcAuPsOd98CYGYvWjgXhZndaGZvm9kiM/tfM/t5WH6fmf3CzBaa2VoLxpy/18xWmtl9rTsxs49bMIb+cjO7M658fZh8Ws9M3jazvxEMgd6pML47w5jeNrOzwvIbzOzJcPsaM/tWWD7aPjhG/S3hGcbVBDcWPRieEXUzs+9ZMB/Bm2b2X0d4jCVHKBFIpnoGKAu/SP/HzM5pWyFsMvm/BGPbnwGMb1OlL3Aa8H8I7qL+MTAROMHMJoevv5NgaPLJwMlm9tE2+5hKMMTEZIK7eE9OMP4Cd58GfBX4Vlz5NOBjwCTgGmszuVI8d38MWAJ8wt0nA90J7qyf6O6TgO8kGIvkOCUCyUjuvo9gwL5ZwHbgkXBQunjTgJc8GKe9iWDIh3h/8uDW+rcIhgN/y91jBMMJjCb4Un/R3bd7MAjhgwSTh8Q7C3jC3fd7MDhZomMutQ4ItzTcV6v57r7T3Q+Edc5M8P0gGOq6HviVmV0FtDsmk0hbSgSSsdy9xd1fdPdvEYwH87FDfIuG8DkWt9y6nuzrZ637a2mzr7ZjvjjBsNvx/1dL2nvDMFlNI5gI5zLgL10SqWQ9JQLJSBbMNRs/JvxkoO3MUouBc8JRGQs49ESxKHz9ADPLJxih8qU2dRYAHw3b50uByw9xH21dZME8td0IZqN6mWDwxEFm1t/Migm+5FvVEUxL2ToPQW93n0vQ3HXiEcYiOUK9hiRT9QT+O+zC2Uww6uIHZr3yYBKU7xJ8oe8CVhE0nyTEgzHgbyUYmtyAp7zNxEfu/pqZPUIwMuU2guRzJBYRzCcwAnjA3ZcAmNkd4baq8OdodR9wt5kdIBhT/0kzKwnjvfkIY5EcodFHJauZWU8PZpYqAJ4A7nX3J6KOqz3hNY5yd78p6lgkt6hpSLLd7Wa2jKCv/TqCaQZFJI7OCEREcpzOCEREcpwSgYhIjlMiEBHJcUoEIiI5TolARCTH/X9f0zKclUyr2wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(sigmoid_inputs, sigmoid_outputs)\n",
    "plt.xlabel(\"Sigmoid Inputs\")\n",
    "plt.ylabel(\"Sigmoid Outputs\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
